--- title: 'Engineering Manager, Kernel Reliability at Cerebras Systems' canonical: 'https://feeny.ai/job/engineering-manager-kernel-reliability-cerebras-systems-united-states-and-0r9hv5eftkh4' type: 'job' last_seen: '2026-09-08' --- # Engineering Manager, Kernel Reliability at Cerebras Systems - **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems) - **Location:** United States and, Canada - **Employment:** full-time - **Posted:** 2026-01-08 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.ashbyhq.com/cerebras/13eec2f8-b308-40b4-8194-f3c133ccb3bc/application **Skills:** Parallel programming, Distributed programming, Message passing, Multicore programming, GPU programming, Embedded programming, Debuggers, Core dump handling, Code sanitizers, Debugging distributed applications, Debugging parallel applications, Deadlock analysis, Livelock analysis, Race condition analysis, Computer architecture, Instruction pipelining, Multithreading, Networking, Monitoring, Reliability engineering > Lead a high-performing engineering team to improve the reliability of Cerebras' advanced compute clusters and underlying services. This hands-on role involves setting technical vision, building diagnostic tools, and collaborating with cross-functional teams to reduce downtime and enhance failure analysis. ## Job description Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ## About The Role We're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you. ## Responsibilities - Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems - Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic - Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis - Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis - Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind - Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution. ## Skills & Qualifications - 6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields - Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.) - Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.) - Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products. ## Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice. ## About Cerebras Systems ## Company Overview - **One-liner**: Cerebras builds wafer-scale AI chips (the largest semiconductors ever made) and supercomputers that deliver up to 15x faster inference than GPUs, offered both on-premises and via cloud APIs. - **Entity Type**: Public (NASDAQ: CBRS) — filed for IPO and now listed on the Nasdaq. - **Headquarters**: Sunnyvale, California, United States - **Founded**: 2015 - **Founders**: Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie, Jean-Philippe Fricker ## Core Business - **Primary industries**: Semiconductor manufacturing, AI computing hardware and software, cloud AI services. - **Target customers**: B2B – enterprises, government research labs, cloud service providers, and AI developers. - **Mission**: “Building impossible technologies so you can too” – accelerating AI through wafer-scale computing. ## Products & Services - **Wafer-Scale Engine (WSE-3)**: The world’s largest AI chip (215 mm²), 58x larger than a typical GPU, built for ultra‑fast AI training and inference. Manufactured by TSMC. - **CS-3 Supercomputer**: A single system powered by the WSE-3, delivering record-breaking AI performance for on-premises deployment. - **Cerebras AI Inference Cloud & Training Cloud**: Pay-as-you‑go APIs that provide drop‑in OpenAI‑compatible access to Cerebras’ hardware for serving, fine‑tuning, and pre‑training models. - **Condor Galaxy Network**: A series of supercomputers (e.g., CG‑1 with 4 exaFLOPs) built in partnership with G42 for high‑performance AI. ## Market Standing - **Valuation/Market Cap**: Not disclosed (recently public; market cap data not available in provided sources). - **Key Metric**: Annual revenue of $78.7 M (latest); total funding of $2.7 B across 15 rounds. - **Notable Investors/Partners**: G42, OpenAI (signed in 2026), Amazon Web Services (signed in 2026), Meta (Llama API), Perplexity, Mistral, Hugging Face, OpenRouter. - **Growth Signals**: - 34.3% YoY headcount growth (701 employees). - Rapid data center expansion across North America and Europe. - Won the HPCwire Readers’ & Editors’ Choice 2025 for Best AI Product/Technology. - Named to Forbes America’s Best Startup Employers 2026 and Fast Company Most Innovative Companies 2026 (AI). ## Competitive Advantages - **Wafer‑scale architecture**: Eliminates interconnect bottlenecks, reducing latency and delivering up to 15x faster inference than GPU clusters. - **Largest AI chip ever built**: 58x larger than any GPU, enabling massive on‑chip memory (SRAM) and compute density. - **Full‑stack offering**: Hardware + cloud APIs + on‑prem systems, giving customers deployment flexibility. - **Strong customer relationships**: Key contracts with OpenAI, AWS, G42, and Mayo Clinic (2024 Gordon Bell Prize work). ## Strategic Focus - **Scale inference capacity**: Building out data centers to become the world’s #1 provider of high‑speed AI inference. - **Deepen cloud partnerships**: Expanding pay‑as‑you‑go cloud access and enterprise deployments. - **Advance wafer‑scale technology**: Continuous R&D on WSE‑3 successors and software stack (compiler, ML workflows). - **Broaden model support**: Already serving Llama, Gemma, Qwen, Mistral, and more; integrating with Hugging Face and OpenRouter. ## Why Work Here - **Culture**: “Extraordinary people, breakthrough innovation, global impact” – the company highlights collaborative, low‑overhead teams with little bureaucracy. - **Work environment**: Hybrid/office with locations in Sunnyvale, San Diego, Toronto, and Bangalore. Inclusive and flexible policy. - **Perks**: Premium medical/dental/vision, life insurance, generous vacation, 401(k) and Group RRSP retirement plans, daily catered meals, healthy snacks, family‑friendly events (including CEO’s famous BBQ). - **Engineering focus**: Tackling fundamental challenges in chip design, system software, compiler technology, and ML workflows. Positions range from hardware (Design Verification, Manufacturing) to software (SRE, Compiler, Cloud). - **Philanthrophy**: Supports local communities and hosts students from around the world for Q&A. ## Sources 1. [cerebras.ai/company](https://www.cerebras.ai/company) 2. [cerebras.ai](https://www.cerebras.ai/) 3. [cerebras.ai/join-us](https://www.cerebras.ai/join-us) 4. [linkedin.com/company/cerebras-systems](https://www.linkedin.com/company/cerebras-systems) ## Other roles at Cerebras Systems - [Network Security Engineer](https://feeny.ai/job/network-security-engineer-cerebras-systems-sunnyvale-s1q0rza0gbsf) — Sunnyvale, CA - [Distributed Software Engineer](https://feeny.ai/job/distributed-software-engineer-cerebras-systems-sunnyvale-2y0byqqxk57d) — Sunnyvale, CA - [AI Inference Core - Infrastructure SW Engineer](https://feeny.ai/job/ai-inference-core-infrastructure-sw-engineer-cerebras-systems-sunnyvale-nbqee273jncn) — Sunnyvale, CA - [AI Inference Core - Senior SW Engineer for Platform & DevOps](https://feeny.ai/job/ai-inference-core-senior-sw-engineer-for-platform-devops-cerebras-systems-06p3hxeg5qb7) — Sunnyvale, CA - [AI Inference Core - SDET Technical Lead, Release Integration Testing](https://feeny.ai/job/ai-inference-core-sdet-technical-lead-release-integration-testing-cerebras-fvqxmj75wav1) — Sunnyvale, CA - [ML Systems Integration Engineer](https://feeny.ai/job/ml-systems-integration-engineer-cerebras-systems-sunnyvale-edvsd91tqp93) — Sunnyvale, CA - [Lead Systems Signal Integrity/Power Integrity Engineer](https://feeny.ai/job/lead-systems-signal-integrity-power-integrity-engineer-cerebras-systems-zqq3c0wfj2v1) — Sunnyvale, CA - [Power Engineering Architect](https://feeny.ai/job/power-engineering-architect-cerebras-systems-sunnyvale-xtzeptb5vdc0) — Sunnyvale, CA - [PCB Layout Engineering Lead](https://feeny.ai/job/pcb-layout-engineering-lead-cerebras-systems-united-states-em00ewnccr6z) — United States - [Network Security Engineer (Remote)](https://feeny.ai/job/network-security-engineer-remote-cerebras-systems-united-states-yfrjb08d4wh9) — United States